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Estimating Risk of Dynamic Trading Strategies from High Frequency Data Flow

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Advances in Data Mining: Applications and Theoretical Aspects (ICDM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9165))

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Abstract

We consider the problem of risk management in the framework of low latency trading. We suggest an efficient method of real-time analysis of massive data flow from the market. The result of the analysis is a new risk measure Dynamic VaR (DVaR) for risk management of low latency trading robots. The work of DVaR is illustrated on a test example and compared with Traditional VaR and ex-post measure commonly used in high frequency trading.

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References

  1. Bachelier, L.: Theorie de la speculation. Ann. Ecole Norm. Sup. 17, 21–86 (1900)

    MATH  MathSciNet  Google Scholar 

  2. Board of Governors of the FRS, 2013 Supervisory Scenarios for Annual Stress Tests Required under the Dodd-Frank Act Stress Testing Rules and the Capital Plan Rule (2012). http://www.federalreserve.gov

  3. Clark, P.K.: A Subordinated Stochastic Process Model of Cotton Futures Prices. Ph.D. Thesis. MA. Harvard University, Cambridge (1970)

    Google Scholar 

  4. Clark, P.K.: A subordinated stochastic process model with finite variance for speculative prices. Econometrica 41, 135–155 (1973)

    Article  MATH  MathSciNet  Google Scholar 

  5. Einstein, A.: On the movement of small particles suspended in a stationary liquid demanded by by the molecular-kinetic theory of heat. Ann. Phys. (Leipzig) 17, 549–560 (1905)

    Article  MATH  Google Scholar 

  6. Embrechts, P., Klüppelberg, C., Mikosch, T.: Measuring Extremal Events for Insurance and Finance. Springer, Heidelberg (2003)

    Google Scholar 

  7. Fama, E.: Mandelbrot and stable paretian hypothesis. J. Bus. 36, 420–429 (1963)

    Article  Google Scholar 

  8. Fama, E.: The behavior of stock market prices. J. Bus. 38, 34–105 (1965)

    Article  Google Scholar 

  9. Gradshteyn, I.S., Ryzhik, I.M.: Table of integrals, series, and products. In: Jeffrey, A., Zwillinger, D., (eds.) Seventh edn. (Feb 2007) 1,171 pages ISBN number: 0-12-373637-4 (2007)

    Google Scholar 

  10. Grandel, J.: Mixed Poisson Processes. Chapman & Hall, London (1997)

    Book  Google Scholar 

  11. Korolev, V.Y.: Probabilistic Methods for the Decomposition of the Volatility of Chaotic Processes. Moscow University Press, Moscow (2011). (in Russian)

    MATH  Google Scholar 

  12. Madan, D., Carr, P., Chang, P.: The variance gamma process and option pricing. Eur. Finan. Rev. 2, 79–105 (1998)

    Article  MATH  Google Scholar 

  13. Mandelbrot, B.B.: The variation of certain speculative prices. J. Bus. 36, 394–419 (1963)

    Article  Google Scholar 

  14. Mandelbrot, B.B.: The variation of some other speculative prices. J. Bus. 40, 393–413 (1967)

    Article  Google Scholar 

  15. Mykland, P.A., Zhang, L.: The double Gaussian approximation for high frequency data. Scand. J. Stat. 38, 215–236 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  16. Mykland, P.A., Zhang, L.: The econometrics of high frequency data. In: Kessler, M., Lindner, A., Sorensen, M. (eds.) Statistical Methods for Stochastic Differential Equations. Chapman and Hall, London (2012)

    Google Scholar 

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Authors and Affiliations

  1. University of Chicago, Chicago, 60637, USA

    Yuri Balasanov

  2. Lomonosov Moscow State University, Moscow, 119991, Russia

    Alexander Doynikov, Victor Lavrent’ev & Leonid Nazarov

Authors
  1. Yuri Balasanov
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  2. Alexander Doynikov
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  3. Victor Lavrent’ev
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  4. Leonid Nazarov
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Corresponding author

Correspondence to Yuri Balasanov .

Editor information

Editors and Affiliations

  1. IBaI, Leipzig, Germany

    Petra Perner

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Balasanov, Y., Doynikov, A., Lavrent’ev, V., Nazarov, L. (2015). Estimating Risk of Dynamic Trading Strategies from High Frequency Data Flow. In: Perner, P. (eds) Advances in Data Mining: Applications and Theoretical Aspects. ICDM 2015. Lecture Notes in Computer Science(), vol 9165. Springer, Cham. https://doi.org/10.1007/978-3-319-20910-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-20910-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20909-8

  • Online ISBN: 978-3-319-20910-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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